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Updated: Feb 13, 2026

Author Spotlight: Advancing the Analysis of Plasma Extracellular Vesicle Proteome for Cardiovascular Biomarker Studies
Published on: January 31, 2025
Extracellular Vesicle Associated Proteomic Biomarkers in Breast Cancer: A Systematic Review and Meta-Analysis
Nahad Al-Mahrouqi1, Hasan Al-Sayegh1, Shoaib Al-Zadjali1
1Research Laboratories, Sultan Qaboos Comprehensive Cancer Care & Research Center, University Medical City, Al Khoud, Muscat 123, Oman.
Abstract:
Breast cancer continues to be the most frequently diagnosed cancer among women worldwide and remains a leading cause of cancer-related mortality. Despite advances in imaging and biopsy-based approaches, current diagnostic methods are invasive, costly, and often insufficient to capture the molecular heterogeneity of tumors. Extracellular vesicles (EVs) have emerged as promising non-invasive biomarkers owing to their role in intercellular communication and their enrichment with tumor-specific cargo. This study conducted a systematic review and meta-analysis of published literature to investigate proteomic alterations in EVs derived from breast cancer samples. From an initial 1097 records screened, four eligible studies were identified, reporting 628 differentially expressed proteins, of which 38 were consistently observed across multiple datasets. Functional enrichment analyses revealed predominant localization of these proteins to vesicle-associated compartments and significant involvement in biological processes related to cell growth, immune regulation, and tumor progression. Pathway analysis further highlighted integrin-mediated interactions, platelet activation, and hemostasis pathways as key molecular mechanisms represented within breast cancer EVs. Overall, the findings reveal a distinct EV proteomic signature in breast cancer that could support early detection and patient monitoring through minimally invasive testing. Future large-scale and standardized studies are needed to validate these candidate proteins and advance EV proteomics toward clinical application in breast cancer management.
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